get_target_prioritization

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotation readOnlyHint=true covers the read-only safety aspect. The description adds a small behavioral detail: the scores are 'compiled across data sources,' indicating an aggregation process. However, it doesn't disclose potential issues like ID format requirements, error behavior, or what the scores represent. With annotations present, this is adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that communicates the core function without any wasted words. It is front-loaded with the main action and object.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (one required param) and has an output schema (so return values are presumed documented), but the description leaves gaps: it doesn't explain what 'prioritisation scores' are, how they are calculated, or why a user would want them. The phrase 'compiled across data sources' is vague and could be expanded to indicate which data sources or how scores should be interpreted. Still, for a simple retrieval tool with one param, it's minimally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the meaning of ensembl_id. While the parameter name is a standard identifier and likely self-explanatory, the description fails to explicitly connect it to the tool's purpose or provide any additional semantics beyond what the name itself conveys.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Return target prioritisation scores compiled across data sources.' It has a specific verb (Return) and resource (target prioritisation scores), and the phrase 'compiled across data sources' helps distinguish it from other target-related tools that return raw data. No other sibling tool mentions prioritisation, making it uniquely identifiable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus its many siblings. It doesn't mention typical use cases, prerequisites, or alternatives. The only hint is the name, but there is no explicit context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.